Abstract
Burst Buffer is an effective solution for reducing the data transfer time and the I/O interference in HPC systems. Extending Burst Buffers (BBs) to handle Big Data applications is challenging because BBs must account for the large data inputs of Big Data applications and the performance guarantees of HPC applications - which are considered as first-class citizens in HPC systems. Existing BBs focus on only intermediate data of Big Data applications and incur a high performance degradation of both Big Data and HPC applications. We present Eley, a burst buffer solution that helps to accelerate the performance of Big Data applications while guaranteeing the performance of HPC applications. In order to improve the performance of Big Data applications, Eley employs a prefetching technique that fetches the input data of these applications to be stored close to computing nodes thus reducing the latency of reading data inputs. Moreover, Eley is equipped with a full delay operator to guarantee the performance of HPC applications - as they are running independently on a HPC system. The experimental results show the effectiveness of Eley in obtaining shorter execution time of Big Data applications (shorter map phase) while guaranteeing the performance of HPC applications.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2017 IEEE International Conference on Cluster Computing, CLUSTER 2017 |
| Publisher | IEEE |
| Pages | 87-91 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781538623268 |
| ISBN (Print) | 9781538623275 |
| DOIs | |
| Publication status | Published - 5 Sept 2017 |
| Event | 2017 IEEE International Conference on Cluster Computing, CLUSTER 2017 - Honolulu, United States Duration: 5 Sept 2017 → 8 Sept 2017 https://ieeexplore.ieee.org/xpl/conhome/8048782/proceeding (Conference Proceedings) |
Publication series
| Name | Proceedings - IEEE International Conference on Cluster Computing, CLUSTER |
|---|---|
| Volume | 2017-September |
| ISSN (Print) | 1552-5244 |
| ISSN (Electronic) | 2168-9253 |
Conference
| Conference | 2017 IEEE International Conference on Cluster Computing, CLUSTER 2017 |
|---|---|
| Country/Territory | United States |
| City | Honolulu |
| Period | 5/09/17 → 8/09/17 |
| Internet address |
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UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
User-Defined Keywords
- HPC
- MapReduce
- Big Data
- Parallel File Systems
- Burst Buffers
- Interference
- Prefetch
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